This is just to remind you about our upcoming HackyHour, which will happen next Tuesday (May 9, 6pm at the Neotopia).
The topic is Tidy Data - strategies to make data cleaning as painless as possible - introduced by Hadley Wickham. He wrote a very influential paper and is maintaining many R packages around this topic.
Here's the paper:
H. Wickham, “Tidy Data,” Journal of Statistical Software, vol. 59, no. 10, 2014. https://doi.org/10.18637/jss.v059.i10
and a link to the many R packages:
http://tidyverse.org/
During my presentation, I will briefly introduce what is actually meant by Tidy Data and present some R tools that will help you to clean up messy data. For those of you who don't have R and RStudio installed I will set up an server hosted by Amazon that will contain all dependencies, and which will be accessible via a web browser. I'll share the link with you when we meet.
See you,
Najko
This is just to remind you about our upcoming HackyHour, which will happen next Tuesday (May 9, 6pm at the Neotopia).
The topic is Tidy Data - strategies to make data cleaning as painless as possible - introduced by Hadley Wickham. He wrote a very influential paper and is maintaining many R packages around this topic.
Here's the paper:
H. Wickham, “Tidy Data,” Journal of Statistical Software, vol. 59, no. 10, 2014. https://doi.org/10.18637/jss.v059.i10
and a link to the many R packages:
http://tidyverse.org/
During my presentation, I will briefly introduce what is actually meant by Tidy Data and present some R tools that will help you to clean up messy data. For those of you who don't have R and RStudio installed I will set up an server hosted by Amazon that will contain all dependencies, and which will be accessible via a web browser. I'll share the link with you when we meet.
See you,
Najko